System and Method for Automatic Selection of Transmission Line Macromodels

ABSTRACT

Transmission line macromodels can be classified into main categories of delay-extraction and rational approximation. The exponential solution of the Telegrapher&#39;s Equation is used to create a system and method that enable a time-domain circuit simulator to automatically select the most appropriate macromodel for a given transmission line structure.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a non-provisional continuation-in-part applicationof U.S. non-provisional patent application Ser. No. 12/058,990, filed onMar. 31, 2008, which is a continuation of U.S. non-provisional patentapplication Ser. No. 10/816,150, filed on Apr. 1, 2004, now U.S. Pat.No. 7,353,155.

FIELD OF THE INVENTION

This invention relates to the design and analysis of interconnectionsbetween electrical systems. More specifically, the invention relates tothe efficient modeling and simulation of multiconductor transmissionlines by automatically selecting macromodels for any given transmissionline structure.

BACKGROUND OF THE INVENTION

High-performance electrical system design requires the use ofsophisticated interconnections between system components. Theseinterconnections must be designed so as to achieve three interrelatedobjectives: minimize signaling delay between components; minimizeelectromagnetic cross talk noise between interconnections; and ensureimmunity to external electromagnetic interferences. Two main examples ofthese interconnections are multiconductor transmission lines andconnectors. The present invention is concerned mainly withmulticonductor transmission lines.

Multiconductor transmission lines are present throughout any electricalsystem comprising several integrated circuits (chips). They are used ona printed circuit board (PCB) for signal transmission between differentchipsets. Multiconductor transmission lines are also used to transfersignals inside a package containing the chip as well as to transfersignals inside the chip itself. PCB and package transmission lines areknown in the art as off-chip transmission lines while the linesresponsible for transferring signals within the chip are known in theart as on-chip transmission lines. The transmission line nature of aninterconnection depends on the wavelength of the signal carried by theinterconnection. With the constant increase in electronic system speed,the signal wavelengths are becoming shorter. The net result is that moreand more of the interconnections are behaving as transmission lines,which makes the task of modeling and analyzing overwhelming. Thesituation is rendered even more complex by the fact that the on-chip andoff-chip transmission lines behave very differently in terms of thelosses (i.e., attenuation and the distortion) incurred by the signalsthey carry. Because of their small cross sections, on-chip transmissionlines are very lossy relative to off-chip transmission lines. Amongoff-chip transmission lines, packaging transmission lines are in generalmore lossy than PCB transmission lines. These differences in location(on-chip, off-chip), length (short, long), losses (high, low), andsignal wavelength make the efficient modeling, simulation, and analysisof transmission lines a difficult engineering task.

There are two main macromodeling approaches used to analyze the behaviorof a transmission line. The first approach is based on a preliminaryextraction of the pure delay (also called time-of-flight delay) incurredby the signal as it is transmitted. An instance of such approach is themethod of characteristics (MoC) (Branin, IEEE Proc. Vol. 55, pp.2012-2013, 1967) and its various generalizations (Gruodis and Chang, IBMJ. of Res. Dev. Vol. 25, pp. 25-41, 1982). The second macromodelingapproach represents the transmission line with a cascade of electricalcells, each cell comprising lumped circuit elements such as resistors,capacitors, and inductors. This approach is equivalent to approximatingthe transfer function of the transmission line, which is atranscendental function, with a rational (i.e., non transcendental)function (e.g. Dounavis et. al., IEEE Transaction on Advanced Packaging,Vol. 22, pp. 382-392, 2000). The first macromodeling approach isreferred to as the delay extraction approach while the secondmacromodeling approach is referred to as the rational approximationapproach.

It is well known in the art (e.g., Elfadel et. al., IEEE Transactions onAdvanced Packaging, Vol. 25, pp. 143-153, 2002) that long, low-losslines, such as coaxial cable (e.g., those connecting processing nodes ina supercomputer) are efficiently simulated using macromodels based ondelay extraction approach. Short, high-loss transmission lines, such ason-chip bus lines (e.g., global bus connecting cable and CPU in amicroprocessor) are efficiently simulated using macromodels based onrational approximation approach. Commercial circuit simulators, such asHSPICE, offer both types of modeling approaches to users. However, thosesimulators require the user to select which approach to use in a givensituation. Users lacking expertise in transmission line theory mayselect the wrong or less efficient transmission line model (e.g.,rational approximation model for a long, lossless line), thus incurringa significant cost in terms of transmission line simulation efficiencyand accuracy. There is therefore a need to develop an automaticselection system and method for transmission line macromodels basedsolely on the physical and geometric characteristics of the transmissionline. Such an automatic selection system can be part of acomputer-aided-design (CAD) tool, such as a circuit simulator, that willhandle all matters related to the efficient and accurate simulation oftransmission lines throughout the electrical system. Such automaticselection will also be crucial for system-level simulation forhigh-performance electronic systems (e.g., mainframe computers) wherethe number of transmission lines is very large and it is not known apriori what type of macromodel is most appropriate for a giventransmission line. The present invention satisfies these needs byproviding a system and method for the automatic selection oftransmission line macromodels.

SUMMARY OF THE INVENTION

The automatic selection is based on the transmission line length, theline per-unit-length parameters, and the maximum frequency of operation.In accordance with the teachings of the present invention, a method andsystem are provided which analyzes the exponential matrix solution ofthe Telegrapher's equation of a transmission line in order to select thebetter and more efficient macromodel to be used for simulatingmulticonductor transmission lines.

The analysis considers the lossy transmission line as a perturbation ofthe lossless transmission line, which behaves as an ideal delay forwhich a delay-based macromodel gives the exact answer very efficiently.Taylor series analysis is then used to derive a mathematical criterionfrom which one can decompose the behavior of the lossy line into a puredelay portion and a pure loss portion. This criterion is then used toderive a critical line length defining the boundary between the twomacromodel efficiency regions: rational approximation macromodel forline lengths below the critical length and delay extraction macromodelfor lines of length above the critical length.

An aspect of this invention is, therefore, the provision of an improvedsystem and method for a computer electrical system design. Anotheraspect of the present invention is the provision of an improved systemand method for computer interconnection system design. A further aspectof the present invention is the provision of an improved system andmethod for computer interconnection system design using macromodeling ofmulticonductor transmission lines. A still further aspect of the presentinvention is the provision of an improved system and method for computerinterconnection system design using automatic macromodel selection of amulticonductor transmission line. A yet further aspect of the presentinvention is the provision of an improved system and method forautomatic macromodel selection of a multiconductor transmission linethat can incorporate in a computer-aided-design tool.

This invention provides a system, a method and a signal bearing mediumthat tangibly embodies a program of machine-readable instructionsexecutable by a digital processing apparatus to perform operations toautomatically select a macromodel from a set of macromodels for use insimulating a transmission line. The operations include providing inputparameters of per-unit-length resistance (R), per-unit-length inductance(L), per-unit-length conductance (G), per-unit-length capacitance (C),length (d), and maximum operating frequency (ω_(max)); computing totaldistortion (Δ_(T)) from the input parameters; providing an errorthreshold (e); comparing the total distortion with the error threshold;and automatically selecting a macromodel based upon whether the totaldistortion is more or less than the error threshold.

This invention further provides a system, a method and a signal bearingmedium that tangibly embodies a program of machine-readable instructionsexecutable by a digital processing apparatus to perform operations toautomatically select a macromodel from a set of macromodels for use insimulating a transmission line. The operations include providing inputparameters of per-unit-length resistance (R), per-unit-lengthcapacitance (C), length (d), and maximum operating frequency (ω_(max)),and error threshold (ε); computing a critical length (d_(critical)) fromthe input parameters; comparing the length of the transmission line withthe critical length; and automatically selecting a macromodel based uponwhether the length of the transmission line is less than or greater thanthe critical length.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 is a schematic diagram of a transmission line represented as atwo-port circuit.

FIG. 2 is a schematic electrical circuit diagram representation of atypical cell of a rational approximation macromodel of a transmissionline.

FIG. 3 is a schematic electrical circuit diagram representation of atypical cell of a delay extraction macromodel of a transmission line.

FIG. 4 is a graphical representation summarizing the CPU efficiency ofthe rational approximation macromodel and delay extraction macromodel ofa transmission line.

FIG. 5 is a flow chart of the overall CAD process for simulation of anelectrical system with several multiconductor transmission lines.

FIG. 6 is a block diagram of a preferred embodiment of an automaticmacromodel selection process incorporating the present invention used inthe CAD system in FIG. 5.

FIG. 7 is a flow chart of an automatic transmission line macromodelselection process comprising the present invention.

DETAILED DESCRIPTION OF THE INVENTION

In order to better understand the significance of the present inventiona brief discussion of the mathematical basis for the automatic selectionof multiconductor transmission line macromodels will now be provided.

Referring now to the figures and to FIG. 1 in particular, there is shownschematically a transmission line 10 as a two-port network with inputsI₁ and V₁ and outputs I₂ and V₂. The port currents I₁(s) and −I₂(s) arerelated to port voltages V₁(s) and V₂(s) by the frequency-domainexponential solution of the Telegrapher's Equation:

$\begin{matrix}{\begin{bmatrix}{- {I_{2}(s)}} \\{V_{2}(s)}\end{bmatrix} = {{{^{- {d{\lbrack{\Phi {(s)}}\rbrack}}}\mspace{14mu}\begin{bmatrix}{I_{1}(s)} \\{V_{1}(s)}\end{bmatrix}}\mspace{14mu} {with}\mspace{14mu} {\Phi (s)}} = \begin{bmatrix}0 & {G + {sC}} \\{R + {sL}} & 0\end{bmatrix}}} & \left( {{eq}.\mspace{14mu} 1} \right)\end{matrix}$

The length of the single transmission line is d, R is theper-unit-length resistance, L is the per-unit-length inductance, G isthe per-unit-length conductance, and C is the per-unit-lengthcapacitance of the transmission line.

The matrix T(s)≡e^(−d[Φ(s)]) is the transfer matrix from the near end(ports 1) 12 to the far end (ports 2) 14 of the transmission line 10.For a single transmission line T(s) is a 2×2 matrix. For amulticonductor transmission line with n lines, the per-unit-lengthparameters are n×n matrices and T(s) is a 2n×2n matrix.

When the line is lossless, R=G=0, and the delay per unit length is givenby τ₀=√{square root over (LC)} and the total line delay is τ=dτ₀.

Assume the transfer matrix of a lossy transmission line can bedecomposed as

$\begin{matrix}\begin{matrix}{{T(s)} \equiv ^{- {d{\lbrack{\Phi {(s)}}\rbrack}}}} \\{= {\exp \left( {- {d\begin{bmatrix}0 & {G + {sC}} \\{R + {sL}} & 0\end{bmatrix}}} \right)}} \\{= {{\exp \left( {- {d\begin{bmatrix}0 & G \\R & 0\end{bmatrix}}} \right)}\mspace{14mu} \exp \mspace{14mu} \left( {- {d\begin{bmatrix}0 & {sC} \\{sL} & 0\end{bmatrix}}} \right)}} \\{\equiv {{T_{delay}(s)}{{T_{loss}(s)}.}}}\end{matrix} & \left( {{eq}.\mspace{14mu} 2} \right)\end{matrix}$

Then one can use a pure delay line to model the delay transfer matrix

${T_{delay}(s)} \equiv {\exp \left( {- {d\begin{bmatrix}0 & {sC} \\{sL} & 0\end{bmatrix}}} \right)}$

and a purely resistive network to model the loss transfer matrix

${T_{loss}(s)} \equiv {\exp \mspace{11mu} {\left( {- {d\begin{bmatrix}0 & G \\R & 0\end{bmatrix}}} \right).}}$

Unfortunately, the above decomposition is not always valid. This isbecause, unlike the scalar case where e^(x+y)=e^(x)e^(y), in the matrixcase e^(A+B)≠e^(A)e^(B) unless the square matrices A and B commute witheach other, i.e., AB=BA. When two matrices do not commute the nonzeromatrix [A, B]=AB−BA is called the commutator of A and B.

For the single conductor line case, denote

$A = {{\begin{bmatrix}0 & G \\R & 0\end{bmatrix}\mspace{14mu} {and}\mspace{14mu} B} = {\begin{bmatrix}0 & C \\L & 0\end{bmatrix}.}}$

Then,

$\left\lbrack {A,B} \right\rbrack = {\begin{bmatrix}{{GL} - {CR}} & 0 \\0 & {{LG} - {RC}}\end{bmatrix}.}$

Note that the above commutator expression is valid for a multiconductorline case. The order of matrix products GL, LG, CR, and RC is important.For single conductor line, the commutator is 0 if and only if GL=CRwhich is the same as LG=RC. This is exactly Heaviside's distortionlessline criteria, which proves the important result that the behavior of adistortionless transmission line can always be decomposed into that of apure delay line and a purely resistive network.

When the line is not distortionless, then it is desirable to find acriterion where equation 2 is approximately satisfied. To derive thiscriterion, first expand T(s) in a Taylor series to the 2nd-order in theline length d, i.e.,

$\begin{matrix}{{T(s)} = {\exp \left( {- {d\begin{bmatrix}0 & {G + {sC}} \\{R + {sL}} & 0\end{bmatrix}}} \right)}} \\{= {\exp\left( {- {d\left\lbrack {A + {sB}} \right\rbrack}} \right.}} \\{\approx {I - {d\left( {A + {sB}} \right)} + \frac{{d^{2}\left( {A + {sB}} \right)}^{2}}{2}}} \\{= {I - {d\left( {A + {sB}} \right)} + \frac{d^{2}\left( {A^{2} + {sAB} + {sBA} + {s^{2}B^{2}}} \right)}{2}}}\end{matrix}$

Similarly, T_(loss)(s) and T_(delay)(s) are expanded into 2nd-orderTaylor series with

$\begin{matrix}{\begin{matrix}{{T_{loss}(s)} = {\exp \left( {- {d\begin{bmatrix}0 & G \\R & 0\end{bmatrix}}} \right)}} \\{= {\exp \; \left( {- {dA}} \right)}} \\{\approx {I - {dA} + \frac{d^{2}A^{2}}{2}}}\end{matrix}{and}} & \left( {{eq}.\mspace{14mu} 4} \right) \\\begin{matrix}{{T_{delay}(s)} = {\exp \left( {- {d\begin{bmatrix}0 & {sC} \\{sL} & 0\end{bmatrix}}} \right)}} \\{= {\exp \left( {- {dsB}} \right)}} \\{\approx {I - {dsB} + \frac{d^{2}s^{2}B^{2}}{2}}}\end{matrix} & \left( {{eq}.\mspace{14mu} 5} \right)\end{matrix}$

Multiplying the expansions of T_(loss)(s) and T_(delay)(s) and droppingterms of order 3 or higher in d, results in

$\begin{matrix}{{{T_{loss}(s)}{T_{delay}(s)}} \approx {I - {d\left( {A + {sB}} \right)} + \frac{d^{2}\left( {A^{2} + {2{sAB}} + {s^{2}B^{2}}} \right)}{2}}} & \left( {{eq}.\mspace{14mu} 6} \right)\end{matrix}$

Define the error matrix

E(s)≡T _(loss)(s)T _(delay)(s)−T(s).  (eq.7)

Then, based on the Taylor series expansions of equation 3 and equation6, the error matrix can be approximated as

$\begin{matrix}{{E(s)} \approx {\frac{{sd}^{2}\left\lbrack {A,B} \right\rbrack}{2}.}} & \left( {{eq}.\mspace{14mu} 8} \right)\end{matrix}$

It follows that when T(s) is approximated with the productT_(loss)(s)T_(delay)(s) the approximation error is proportional to thematrix commutator [A, B]. This is in line with the distortionless casewhere the zero commutator guarantees that the error is also zero.Another interesting observation is that the error is proportional tos=jω, where ω is the frequency of operation, and quadratic in the lengthof the line. In other words, line length has more impact on theapproximation error than the frequency range of operation.

Let now ε>0 be a required upper bound on this approximation error. Bytaking the matrix norms of equation 8, using the ε upper bound, andreplacing s with jω_(max), where ω_(max) is the maximum operatingfrequency, the conclusion is that the inequality

$\begin{matrix}{{\frac{{sd}^{2}\left\lbrack {A,B} \right\rbrack}{2}} = {{\omega_{\max}d^{2}{\left\lbrack {A,B} \right\rbrack }} < ɛ}} & \left( {{eq}.\mspace{14mu} 9} \right)\end{matrix}$

must be satisfied in order to guarantee that the decomposition error isbelow the error threshold throughout the frequency range. Note that thecommutator matrix norm is

∥[A,B]∥=max(∥GL−CR∥,∥LG−RC∥)

and that for the single line case, this norm reduces to

∥[A,B]∥=|LG−RC|.

Another simplification is the case when the per-unit-length conductanceis zero (e.g., on-chip transmission lines) in which case ∥[A, B]∥=RC andthe error criterion becomes

$\begin{matrix}{{\frac{{sd}^{2}\left\lbrack {A,B} \right\rbrack}{2}} = {\frac{\omega_{\max}d^{2}{RC}}{2} < ɛ}} & \left( {{eq}.\mspace{14mu} 10} \right)\end{matrix}$

Based on equation 10, define the critical line length as

d _(critical)=√{square root over (2ε/(ω_(max) RC))}  (eq. 11)

This is the length above which the approximation error becomesunacceptable. To recover the accuracy, the line must be segmented intosegments of length less than the critical length. Some implementationsof the method of characteristics require such segmentation especiallyfor very lossy lines. This segmentation has a negative impact on theefficiency of the transmission line macromodel. An interestingobservation consistent with past heuristic experience is that thecritical length for the method of characteristic macromodel is inverselyproportional to the resistive losses per unit length of the line.Furthermore, higher frequencies require smaller line segments.

An alternative interpretation of equation 10 is that delay extraction isneeded only if the length of the line is above the critical length. Forlines with d<d_(critical) a rational approximation macromodel satisfiesthe required accuracy.

Having now set forth the basis for the selection of the transmissionline length at which either one of the delay extraction macromodel orthe rational approximation macromodel is the preferred macromodel forsimulating transmission lines, preferred embodiments of a system andmethod for automatically making the selection of which of themacromodels to use for simulating a multiconductor transmission linewill now be described.

FIG. 2 is a schematic representation of a typical electrical cell 20 ofa rational assumption macromodel of a transmission line. The fullmacromodel is a cascade of such cells. The cell circuit element valuesof Rs 22, Ls 24, Gs/2 26, and Cs/2 28 are derived from the transmissionline length d, the number of cells and the per-unit-length R, L, G, andC values. The rational assumption macromodel of a transmission line isone preferred approach for simulating a transmission line.

FIG. 3 is a schematic representation of a typical electrical circuitrepresentation 300 of a delay extraction macromodel of a transmissionline. This macromodel relates the voltage-current pair at the near end(V₁, I₁) 302 of the circuit 300 to the voltage-current pair at the farend (V₂, I₂) 304 of the circuit 300. The values Y₁ 306 and Y₂ 308 of thecircuit 300 are admittance derived from the transmission line. Thevalues J₁ 310 and J₂ 312 of the circuit 300 are controlled currentsources. The extracted delay of the macromodel is implicit in the valuesJ₁ and J₂. The delay extraction macromodel of a transmission line isanother preferred approach for simulating a transmission line.

FIG. 4 is a graphical representation summarizing the CPU efficiency oftwo preferred categories of transmission line macromodels, i.e. delayextraction macromodel and rational assumption macromodel. The delayextraction macromodel is more efficient for simulating long, low-losstransmission lines. The rational assumption macromodel is more efficientfor simulating short, high-loss transmission lines. The crossover point40 is not known a priori.

The problem encountered with using macromodels to simulate transmissionlines occurs when a user is required to select the more efficientmacromodel to be used for simulating transmission lines. The presentinvention provides a system and method for the automatic selection ofthe more efficient macromodel for a particular transmission linestructure.

The flow chart in FIG. 5 shows an overall CAD process 500 for simulationof an electrical system having several multiconductor transmissionlines. First, an input 502 describing the electrical circuit to besimulated (e.g., SPICE file) is provided as an input to the CAD system.The CAD system may be any conventional CAD system known in the art.Then, for each transmission line in the inputted file, an automaticmacromodel selection is performed 504 in accordance with the processdescribed in conjunction with FIG. 6 below. After applying theautomatically selected macromodel, an output 506 is provided which isthe circuit simulation result using the cells in either FIG. 2 or 3corresponding to the selected macromodel.

A preferred embodiment of an automatic macromodel selection process 600used in step 504 of FIG. 5 is shown in the block diagram of FIG. 6.

Transmission line parameters, including the per-unit-length R, L, G, andC values, the transmission line length d, the maximum operatingfrequency ω_(max) and the model error threshold ε are provided as inputs602 to an automatic transmission line macromodel selection system 604.Using the inputted parameters, an automatic transmission line macromodelselection decision process 604, in accordance with the flow chart shownin FIG. 7 and described below, is performed.

After making the macromodel selection decision, a transmission linemacromodel is generated 606 and provided to an electrical circuitsimulator program 608. Optionally, macromodel information frommacromodel database 610 is provided to the electrical circuit simulatorprogram 608 in accordance with the selected macromodel. Electricalterminations of the transmission line (drivers and receivers) at thenear and far ends of the transmission line and other circuitryinformation (e.g., reference nodes for the near and far ends) 612 arealso provided as input to the electrical circuit simulator program 608.The electrical circuit simulator program 608 provides output waveformsand electrical circuit figures of merit related to the transmission lineto be simulated 614. The output waveforms and electrical circuit figuresof merit are used to provide the circuit simulation results in step 506.

FIG. 7 is a flow chart of an automatic transmission line macromodelselection decision process 700, the result of which is used in block 604of FIG. 6 for selecting the more efficient macromodel to be used tosimulate the transmission line.

The multiconductor transmission line per-unit-length R, L, G, and Cparameter values 702 are provided as inputs to be used to compute 704the transmission line distortion per-unit-length: Δ=max(∥GL−CR∥,∥LG−RC∥).

The computed distortion per-unit-length Δ from step 704, thetransmission line length d from block 706, and the maximum operatingfrequency ω_(max) from block 708 are provided as inputs to compute thetotal distortion 710:

$\Delta_{T} = {\frac{\Delta \; d^{2}\omega_{\max}}{2}.}$

The computed total distortion Δ_(T) from block 710 and an errorthreshold e from block 712 are compared at step 714. If Δ_(T)<e, thedelay extraction macromodel is selected 716 and used in step 604 in FIG.6. If Δ_(T)>e, then the rational assumption macromodel is selected 718and used in step 604 in FIG. 6.

While the delay-extraction macromodel and the rational approximationmacromodel are preferred simulation models, it will be apparent to thoseskilled in the art that other macromodels may be included for selectionaccording to appropriate criteria.

In an embodiment, the values of per-unit-length parameters R, G, L, andC may be modeled to change with frequency to account for such physicalphenomena as proximity effects and skin effects. In another embodiment,parameters may include values to model hysteresis effects and/orparasitic capacitances. In yet another embodiment, the R, L, G, and Cper-unit length parameters may be input in a simulation model in theform of matrices; that is, these parameters may be input in the form ofsquare tables of scalars rather than as scalars. Expressing theparameters as matrices for input into the macromodel is especiallybeneficial for modeling a transmission system of multiple conductors. Instill another embodiment, values may be input for an operatingtemperature, an operating temperature range, voltage, current, thetopology or layout of multiple conductors, aging, environmental factors,and the like. Combinations of the above embodiments are contemplated.

The automatic selection of efficient transmission line macromodels inaccordance with the teachings of the present invention may be performedon a general purpose computer. Preferably, the automatic selectionprocess is used in conjunction with a CAD system or CAD program. Theautomatic selection process obviates the requirement of a user to selectthe most efficient transmission line macromodel for a particularmulticonductor transmission line to be simulated.

While there has been described and illustrated a preferred embodiment ofa system and method for the automatic selection of transmission linemacromodels, it will be apparent to those skilled in the art thatmodifications and variations are possible without deviating from thebroad teachings and spirit of the present invention which shall belimited solely by the scope of the claims appended hereto.

1. A computer modeling system comprising: a processor that has at leastone input that receives parameters related to one or more electricaltransmission lines, the parameters representing one or more physicalcharacteristics and one or more electrical characteristics of the one ormore electrical transmission lines; a database with a set of one or moremacromodels that in which the processor is arranged to apply theparameters in a simulation to determine an electrical behavior of one ormore of the electrical transmission lines, wherein the appliedparameters comprise at least one of at least one parameter that variesaccording to frequency and at least one parameter that is input as amatrix; and an automatic selection process controlled by the processorthat selects a macromodel from the set of macromodels to simulate one ormore of the electrical transmission lines, the selection of themacromodel being determined by one of comparing a total distortion to anerror threshold, wherein the processor provides a generated transmissionline macromodel corresponding to the selected macromodel to anelectrical circuit simulator program.
 2. A computer modeling system asin claim 1, wherein the processor uses a matrix norm of at least some ofthe parameters in determining the total distortion.
 3. A computermodeling system as in claim 2, wherein the processor also uses anoperational frequency and a transmission line length to determine thetotal distortion.
 4. A computer modeling system as in claim 1, furthercomprising the electrical circuit simulator program and providingelectrical terminations of the one or more transmission lines as aninput to the electrical circuit simulator program.
 5. A computermodeling system comprising: a processor that has at least one input thatreceives parameters related to one or more electrical transmissionlines, the parameters representing one or more physical characteristicsand one or more electrical characteristics of the one or more electricaltransmission lines; a database with a set of one or more macromodelsthat in which the processor is arranged to apply the parameters in asimulation to determine an electrical behavior of one or more of theelectrical transmission lines, wherein the applied parameters compriseat least one of at least one parameter that varies according tofrequency and at least one parameter that is input to the simulation inmatrix form; and an automatic selection process controlled by theprocessor that selects a macromodel from the set of macromodels tosimulate one or more of the electrical transmission lines, the selectionof the macromodel being determined by one of comparing a length of thetransmission line to a critical length calculated from the parameters,wherein the processor provides a generated transmission line macromodelcorresponding to the selected macromodel to an electrical circuitsimulator program.
 6. A computer modeling system as in claim 5, whereinthe parameters include an operational frequency.
 7. A computer modelingsystem as in claim 5, further comprising the electrical circuitsimulator program.
 8. A computer modeling system as in claim 5, whereinthe at least one input is provided in a file.
 9. A computer readablemedium embodied with a computer program of machine-readable instructionsexecutable by a digital processing apparatus to perform operations toautomatically select a macromodel from a set of macromodels for use insimulating a transmission line, the operations comprising: providinginput parameters of physical dimensions, electrical characteristics, andmaximum operating frequency (ω_(max)), wherein the input parameterscomprise, wherein the input parameters comprise at least one of aparameter whose value varies according to frequency and a parameterinput to the simulation in matrix form, computing total distortion(Δ_(T)) from the input parameters; providing an error threshold (e);comparing the total distortion with the error threshold; automaticallyselecting a macromodel based upon whether the total distortion is moreor less than the error threshold.
 10. A computer readable medium as setforth in claim 9, wherein the macromodel is selected from one of a delayextraction macromodel and a rational approximation macromodel.
 11. Acomputer readable medium according to claim 9, used in acomputer-aided-design (CAD) system.
 12. A computer readable mediumembodied with a computer program of machine-readable instructionsexecutable by a digital processing apparatus to perform operations toautomatically select a macromodel from a set of macromodels for use insimulating one or more transmissions line, the operations comprising:providing input parameters of physical dimensions, electricalcharacteristics, maximum operating frequency (ω_(max)) and errorthreshold (ε), wherein the input parameters comprise at least one of aparameter whose value varies according to frequency and a parameterinput to the simulation in matrix form; computing a critical length(d_(critical)) from the input parameters; comparing the length of thetransmission line with the critical length; automatically selecting amacromodel based upon whether the length of the transmission line isless than or greater than the critical length.
 13. A computer readablemedium as set forth in claim 12, wherein the macromodel is selected fromone of a delay extraction macromodel and a rational approximationmacromodel.
 14. A computer readable medium according to claim 12 used ina computer-aided-design (CAD) system.
 15. A computer readable medium asset forth in claim 12, wherein the electrical characteristics are inputin a file.
 16. A computer readable medium as set forth in claim 12,further comprising proving an output from the selected macromodel as aninput to an electrical circuit simulator program.
 17. A computerreadable medium as set forth in claim 1, wherein at least some of theparameters are in matrix form.
 18. A computer readable medium as setforth in claim 1, wherein at least some of the parameters vary withfrequency.
 19. A computer readable medium as set forth in claim 1,wherein all the parameters are in matrix form.
 20. A computer readablemedium as set forth in claim 1, wherein all the parameters vary withfrequency.